Laser peening without coating—an advanced surface treatment: A review

Laser peening without protective coating (LPwC) is an advanced mechanical surface modification method being used for a wide range of metallic materials for improving their fatigue and corrosion properties. The literature review of LPwC for the last two decades is systematically presented. The mechanism and experimental parameters of LPwC are described comprehensively. The major factors that influence the fatigue or corrosion properties, for example, compressive residual stress (CRS) and surface roughness, are analyzed with great care using the available data from the literature. A list of suggestions for future work in LPwC is given at the end.     

Energy Prediction in IoT Systems Using Machine Learning Models

The Internet of Things (IoT) technology has been developed for directing and maintaining the atmosphere in smart buildings in real time. In order to optimise the power generation sector and schedule routine maintenance, it is crucial to predict future energy demand. Electricity demand forecasting is difficult because of the complexity of the available demand patterns. Establishing a perfect prediction of energy consumption at the building’s level is vital and significant to efficiently managing the consumed energy by utilising a strong predictive model. Low forecast accuracy is just one of the reasons why energy consumption and prediction models have failed to advance. Therefore, the purpose of this study is to create an IoT-based energy prediction (IoT-EP) model that can reliably estimate the energy consumption of smart buildings. A real-world test case on power predictions is conducted on a local electricity grid to test the practicality of the approach. The proposed (IoT-EP) model selects the significant features as input neurons, the predictable data is selected as output nodes, and a multi-layer perceptron is constructed along with the features of the Convolution Neural Network (CNN) algorithm. The analysis of the proposed IoT-EP model has higher accuracy of 90%, correlation of 89%, and variance of 16% in less training time of 29.2 s, and with a higher prediction speed of 396 (observation/sec). When compared to existing models, the results showed that the proposed (IoT-EP) model outperforms with a satisfactory level of accuracy in predicting energy consumption in smart buildings.     

Reductive dechlorination of 3,3',4,4'-tetrachlorobiphenyl (PCB77) using palladium or palladium/iron nanoparticles and assessment of the reduction in toxic potency in vascular endothelial cells

Palladium-based nanoparticles immobilized in polymeric matrices were applied to the reductive dechlorination of 3,3',4,4'-tetrachlorobiphenyl (PCB77) at room temperature. Two different dechlorination platforms were evaluated using (1) Pd nanoparticles within conductive polypyrrole films; or (2) immobilized Fe/Pd nanoparticles within polyvinylidene fluoride microfiltration membranes. For the first approach, the polypyrrole film was electrochemically formed in the presence of perchlorate ions that were incorporated into the film to counter-balance the positive charges of the polypyrrole chain. The film was then incubated in a solution containing tetrachloropalladate ions, which were exchanged with the perchlorate ions within the film. During this exchange, reduction of tetrachloropalladate by polypyrrole occurred, which led to the formation of palladium nanoparticles within the film. For the second approach, the membrane-supported Fe/Pd nanoparticles were prepared in three steps: polymerization of acrylic acid in polyvinylidene fluoride microfiltration membrane pores was followed by ion exchange of Fe(2+), and then chemical reduction of the ferrous ions bound to the carboxylate groups. The membrane-supported iron nanoparticles were then soaked in a solution of tetrachloropalladate resulting in the deposition of Pd on the Fe surface. The nanoparticles prepared by both approaches were employed in the dechlorination of PCB77. The presence of hydrogen was required when the monometallic Pd nanoparticles were employed. The results indicate the removal of chlorine atoms from PCB77, which led to the formation of lower chlorinated intermediates and ultimately biphenyl. Toxicity associated with vascular dysfunction by PCB77 and biphenyl was compared using cultured endothelial cells. The data strongly suggest that the dechlorination system used in this study markedly reduced the proinflammatory activity of PCB77, a persistent organic pollutant.     

Compact circularly polarized beam‐switching wireless power transfer system for ambient energy harvesting applications

In this work, we propose a circularly polarized (CP) beam‐switching wireless power transfer system for ambient energy harvesting applications operating at 2.4 GHz. Beam‐switching is achieved using a low profile, electrically small CP antenna array with four elements and a novel miniaturized 4× 4 butler matrix. The CP antenna is designed with an e‐shaped slot and four antennas. The CP antenna measures 0.32 λ₀× 0.32 λ₀× 0.006 λ₀ at 2.4 GHz. The antenna has a gain of 3 dBic and an axial ratio less than 3‐dB at 2.4 GHz. A linear antenna array consisting of four elements is designed with the CP antenna element with an inter‐element distance of 0.29 λ₀ . A 4× 4 butler matrix with miniaturized couplers and crossovers are used to feed the four antenna array elements. Based on the input port of excitation, the main beam of the antenna array is demonstrated to be switched to four directions: ?5°, 65°, ?55°, and 20°. A CP rectenna is used to demonstrate the wireless power transfer capability of the combination of the butler matrix and the CP‐antenna array. The rectenna consists of a Teo‐shaped CP antenna and a rectifier. The open circuit voltage at the output of the rectenna is found to peak value of 30 mV at ?3°, 61°, ?53°, and 17°. Thus a complete system for CP wireless power transfer including the power transmission system as well as the RF energy harvesting sensor is designed and experimentally verified.     

Context Aware Trust Management Scheme for Pervasive Healthcare

Wireless Personal Communications - Medical sensor nodes are used in pervasive healthcare applications like remote patient monitoring, elderly care to collect patients vital signs for identifying...     

Heat-Affected Zone Liquation Cracking Resistance of Friction Stir Processed Aluminum-Copper Alloy AA 2219

Metallurgical and Materials Transactions B - In the current work, the effect of friction stir processing on heat-affected zone (HAZ) liquation cracking resistance of aluminum-copper alloy AA 2219...     

Use of Friction Stir Processing for Improving Heat-Affected Zone Liquation Cracking Resistance of a Cast Magnesium Alloy AZ91D

Metallurgical and Materials Transactions B - In this work, a cast magnesium alloy AZ91D was friction stir processed. Detailed microstructural studies and Gleeble hot ductility tests were conducted...     

Green synthesized N-doped graphitic carbon sheets coated carbon cloth as efficient metal free electrocatalyst for hydrogen evolution reaction

Heteroatom doped carbon structures received a great attention owing to its applications in catalysis, energy and optics. In this work, a simple hydrothermal approach for the synthesis of nitrogen doped graphitic carbon sheets (N-GCSs) is reported. Rubus parvifolius (R. parvifolius) fruit juice and aqueous ammonia are used as carbon precursor and nitrogen dopant, respectively. The synthesized N-GCSs are characterized using Fourier transform infrared (FT-IR) spectroscopy, X-ray photoelectron spectroscopy (XPS), X-ray diffraction (XRD), Raman spectroscopy, high resolution transmission electron microscopy (HR-TEM) and field emission scanning electron microscopy (FE-SEM) coupled with energy dispersive spectrum (EDS). The presence of hydroxyl and carbonyl functionalities in the synthesized N-GCSs are confirmed by the FT-IR analysis. The doping of nitrogen in N-GCSs is revealed through the XPS spectrum. The XRD and Raman studies imply that the synthesized N-GCSs are moderate graphitic nature. The FE-SEM and HR-TEM images of N-GCSs exposed its sheet like porous morphology. The electrocatalytic activity of N-GCSs coated carbon cloth (N-GCSs/CC) are examined towards hydrogen evolution reaction (HER) in 0.50 M H₂SO₄ using linear sweep voltammetry (LSV), Tafel and electrochemical impedance spectroscopy (EIS) studies. The onset potential of synthesized N-GCSs/CC is about ?0.25 V_RHE, which is lower than that of bare carbon cloth (CC) ?0.75 V_RHE. The Tafel slope of N-GCSs/CC is smaller (198 mV dec^?1) than that of bare CC (253 mV dec^?1), suggested fast kinetics of N-GCSs. Moreover, the N-GCSs/CC is attained ?10 mA cm^?2 of current density at very low over potential of ?0.320 V_RHE. The EIS studies also proved the excellent catalytic activity of N-GCSs/CC towards HER. Thus, the R. parvifolius derived N-GCSs is a better candidate for HER in acidic medium.     

Attempting to Model a Fresh Three Dimensional Coverage Scheme for Wireless Sensor Networks

Wireless Personal Communications - The coverage framework and the installation policies are straightforwardly linked to the feasible distribution of the restricted resources for the wireless sensor...     

RETRACTED ARTICLE: Designing statistical assessment healthcare information system for diabetics analysis using big data

Health services research provides a multi-disciplinary area of scientific exploration in relation to financial systems, social factors, organizational processes, and health technologies. With the help of big data, the huge amount of data can well be stored and handled effectively for diagnosis and also proper treatment of diseases can be monitored with these emerging technologies. In recent years, Diabetes Mellitus is non-transmittable illnesses that are a matter of concern in most of the developing countries. This paper proposes a model of a statistical assessment, healthcare information system for Diabetes Analysis employing big data. The performance metric such as accuracy and F-measure for the proposed statistical assessment model is evaluated by Hadoop framework, the results are comparatively higher than existing methods.